@inproceedings{SteinkeGehrkeDzido2009,
author = {Steinke, Karl-Heinz and Gehrke, Martin and Dzido, Robert},
title = {Writer Recognition by Combining Local and Global Methods},
url = {http://nbn-resolving.de/urn:nbn:de:bsz:960-opus-2867},
year = {2009},
abstract = {The research project "Herbar Digital" was started in 2007 with the aim to digitize 3.5 million dried plants on paper sheets belonging to the Botanic Museum Berlin in Germany. Frequently the collector of the plant is unknown, so a procedure had to be developed in order to determine the writer of the handwriting on the sheet. In the present work the static character was transformed into a dynamic form. This was done with the model of an inert ball which was rolled along the written character. During this off-line writer recognition, different mathematical procedures were used such as the reproduction of the write line of individual characters by Legendre polynomials. When only one character was used, a recognition rate of about 40\% was obtained. By combining multiple characters, the recognition rate rose considerably and reached 98.7\% with 13 characters and 93 writers (chosen randomly from the international IAM-database [3]). A global statistical approach using the whole handwritten text resulted in a similar recognition rate. By combining local and global methods, a recognition rate of 99.5\% was achieved.},
subject = {Herbarium},
language = {en}
}
@inproceedings{GehrkeSteinkeDzido2009,
author = {Gehrke, Martin and Steinke, Karl-Heinz and Dzido, Robert},
title = {Writer recognition by characters, words and sentences},
url = {http://nbn-resolving.de/urn:nbn:de:bsz:960-opus-2873},
year = {2009},
abstract = {The methods developed in the research project "Herbar Digital" are to help plant taxonomists to master the great amount of material of about 3.5 million dried plants on paper sheets belonging to the Botanic Museum Berlin in Germany. Frequently the collector of the plant is unknown. So a procedure had to be developed in order to determine the writer of the handwriting on the sheet. In the present work the static character is transformed into a dynamic form. This is done with the model of an inert ball which is rolled through the written character. During this off-line writer recognition, different mathematical procedures are used such as the reproduction of the write line of individual characters by Legendre polynomials. When only one character is used, a recognition rate of about 40\% is obtained. By combining multiple characters, the recognition rate rises considerably and reaches 98.7\% with 13 characters and 93 writers (chosen randomly from the international IAM-database [3]). Another approach tries to identify the writer by handwritten words. The word is cut out and transformed into a 6-dimensional time series and compared e.g. by means of DTW-methods. A global statistical approach using the whole handwritten sentences results in a similar recognition rate of more than 98\%. By combining the methods, a recognition rate of 99.5\% is achieved.},
subject = {Herbarium},
language = {en}
}
@inproceedings{SteinkeDzidoGehrkeetal.2008,
author = {Steinke, Karl-Heinz and Dzido, Robert and Gehrke, Martin and Pr{\"a}tel, Klaus},
title = {Feature recognition for herbarium specimens (Herbar-Digital)},
url = {http://nbn-resolving.de/urn:nbn:de:bsz:960-opus-2888},
year = {2008},
abstract = {Our research project, "Rationalizing the virtualization of botanical document material and their usage by process optimization and automation (Herbar-Digital)" started on July 1, 2007 and will last until 2012. Its long-term aim is the digitization of the more than 3,5 million specimens in the Berlin Herbarium. The University of Applied Sciences and Arts in Hannover collaborates with the department of Biodiversity Informatics at the BGBM (Botanic Garden and Botanical Museum Berlin-Dahlem) headed by Walter Berendsohn. The part of Herbar-Digital here presented deals with the analysis of the generated high resolution images (10,400 lines x 7,500 pixel).},
subject = {Herbarium},
language = {en}
}
@inproceedings{DzidoGehrkeSteinke2009,
author = {Dzido, Robert and Gehrke, Martin and Steinke, Karl-Heinz},
title = {Erkennung von Schreibern mittels handgeschriebener Buchstaben},
url = {http://nbn-resolving.de/urn:nbn:de:bsz:960-opus-2858},
year = {2009},
abstract = {Das Forschungsprojekt „Herbar Digital" [JKS00] startete 2007 mit dem Ziel der Digitalisierung des Bestands von mehr als 3,5 Millionen getrockneter Pflanzen bzw. Pflanzenteile auf Papierb{\"o}gen (Herbarbelege) des Botanischen Museums Berlin. Da gelegentlich der Sammler der Pflanze unbekannt ist, wurde in der vorliegenden Arbeit ein Verfahren entwickelt, um aus kursiv geschriebenen Buchstaben deren Schreiber zu bestimmen. Dazu muss der statische Buchstabe in eine dynamische Form gebracht werden. Dies geschieht mit dem Modell einer tr{\"a}gen Kugel, die durch den Schriftzug rollt. Bei dieser Offline-Schreibererkennung werden verschiedene Verfahren wie die Nachbildung der Schreiblinie einzelner Buchstaben durch z.B. Legendre-Polynome verwendet. Bei Verwendung nur eines Buchstabens der Schreiber wird eine Erkennungsrate von durchschnittlich 40\% erreicht. Durch Kombination von mehreren Buchstaben steigt die Erkennungsrate stark an und betr{\"a}gt bei 13 Buchstaben und 93 Schreibern einer internationalen Datenbank 98,6\%.},
subject = {Herbarium},
language = {de}
}